Archive for the ‘Population Health Management, Genetics & Pharmaceutical’ Category

Decline in Sperm Count – Epigenetics, Well-being and the Significance for Population Evolution and Demography


Dr. Marc Feldman, Expert Opinion on the significance of Sperm Count Decline on the Future of Population Evolution and Demography

Dr. Sudipta Saha, Effects of Sperm Quality and Quantity on Human Reproduction

Dr. Aviva Lev-Ari, Psycho-Social Effects of Poverty, Unemployment and Epigenetics on Male Well-being, Physiological Conditions affecting Sperm Quality and Quantity


Recent studies concluded via rigorous and comprehensive analysis found that Sperm Count (SC) declined 52.4% between 1973 and 2011 among unselected men from western countries, with no evidence of a ‘leveling off’ in recent years. Declining mean SC implies that an increasing proportion of men have sperm counts below any given threshold for sub-fertility or infertility. The high proportion of men from western countries with concentration below 40 million/ml is particularly concerning given the evidence that SC below this threshold is associated with a decreased monthly probability of conception.

1.Temporal trends in sperm count: a systematic review and meta-regression analysis 

Hagai Levine, Niels Jørgensen, Anderson Martino‐Andrade, Jaime Mendiola, Dan Weksler-Derri, Irina Mindlis, Rachel Pinotti, Shanna H SwanHuman Reproduction Update, July 25, 2017, doi:10.1093/humupd/dmx022.


2. Sperm Counts Are Declining Among Western Men – Interview with Dr. Hagai Levine

3. Trends in Sperm Count – Biological Reproduction Observations

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

4. Long, mysterious strips of RNA contribute to low sperm count – Long non-coding RNAs can be added to the group of possible non-structural effects, possibly epigenetic, that might regulate sperm counts.

Dynamic expression of long non-coding RNAs reveals their potential roles in spermatogenesis and fertility

Published: 29 July 2017
Thus, we postulated that some lncRNAs may also impact mammalian spermatogenesis and fertility. In this study, we identified a dynamic expression pattern of lncRNAs during murine spermatogenesis. Importantly, we identified a subset of lncRNAs and very few mRNAs that appear to escape meiotic sex chromosome inactivation (MSCI), an epigenetic process that leads to the silencing of the X- and Y-chromosomes at the pachytene stage of meiosis. Further, some of these lncRNAs and mRNAs show strong testis expression pattern suggesting that they may play key roles in spermatogenesis. Lastly, we generated a mouse knock out of one X-linked lncRNA, Tslrn1 (testis-specific long non-coding RNA 1), and found that males carrying a Tslrn1 deletion displayed normal fertility but a significant reduction in spermatozoa. Our findings demonstrate that dysregulation of specific mammalian lncRNAs is a novel mechanism of low sperm count or infertility, thus potentially providing new biomarkers and therapeutic strategies.

This article presents two perspectives on the potential effects of Sperm Count decline.

One Perspective identifies Epigenetics and male well-being conditions

  1. as a potential explanation to the Sperm Count decline, and
  2. as evidence for decline in White male longevity in certain geographies in the US since the mid 80s.

The other Perspective, evaluates if Sperm Count Decline would have or would not have a significant long term effects on Population Evolution and Demography.

The Voice of Prof. Marc Feldman, Stanford University – Long term significance of Sperm Count Decline on Population Evolution and Demography

Poor sperm count appears to be associated with such demographic statistics as life expectancy (1), infertility (2), and morbidity (3,4). The meta-analysis by Levine et al. (5) focuses on the change in sperm count of men from North America, Europe, Australia, and New Zealand, and shows a more than 50% decline between 1973 and 2011. Although there is no analysis of potential environmental or lifestyle factors that could contribute to the estimated decline in sperm count, Levine et al. speculate that this decline could be a signal for other negative changes in men’s health.

Because this study focuses mainly on Western men, this remarkable decline in sperm count is difficult to associate with any change in actual fertility, that is, number of children born per woman. The total fertility rate in Europe, especially Italy, Spain, and Germany, has slowly declined, but age at first marriage has increased at the same time, and this increase may be more due to economic factors than physiological changes.

Included in Levine et al.’s analysis was a set of data from “Other” countries from South America, Asia, and Africa. Sperm count in men from these countries did not show significant trends, which is interesting because there have been strong fertility declines in Asia and Africa over the same period, with corresponding increases in life expectancy (once HIV is accounted for).

What can we say about the evolutionary consequences for humans of this decrease? The answer depends on the minimal number of sperm/ml/year that would be required to maintain fertility (per woman) at replacement level, say 2.1 children, over a woman’s lifetime. Given the smaller number of ova produced per woman, a change in the ovulation statistics of women would be likely to play a larger role in the total fertility rate than the number of sperm/ejaculate/man. In other words, sperm count alone, absent other effects on mortality during male reproductive years, is unlikely to tell us much about human evolution.

Further, the major declines in fertility over the 38-year period covered by Levine et al. occurred in China, India, and Japan. Chinese fertility has declined to less than 1.5 children per woman, and in Japan it has also been well below 1.5 for some time. These declines have been due to national policies and economic changes, and are therefore unlikely to signal genetic changes that would have evolutionary ramifications. It is more likely that cultural changes will continue to be the main drivers of fertility change.

The fastest growing human populations are in the Muslim world, where fertility control is not nearly as widely practiced as in the West or Asia. If this pattern were to continue for a few more generations, the cultural evolutionary impact would swamp any effects of potentially declining sperm count.

On the other hand, if the decline in sperm count were to be discovered to be associated with genetic and/or epigenetic phenotypic effects on fetuses, newborns, or pre-reproductive humans, for example, due to stress or obesity, then there would be cause to worry about long-term evolutionary problems. As Levine et al. remark, “decline in sperm count might be considered as a ‘canary in the coal mine’ for male health across the lifespan”. But to date, there is little evidence that the evolutionary trajectory of humans constitutes such a “coal mine”.


  1. Jensen TK, Jacobsen R, Christensen K, Nielsen NC, Bostofte E. 2009. Good semen quality and life expectancy: a cohort study of 43,277 men. Am J Epidemiol 170: 559-565.
  2. Eisenberg ML, Li S, Behr B, Cullen MR, Galusha D, Lamb DJ, Lipshultz LI. 2014. Semen quality, infertility and mortality in the USA. Hum Reprod 29: 1567-1574.
  3. Eisenberg ML, Li S, Cullen MR, Baker LC. 2016. Increased risk of incident chronic medical conditions in infertile men: analysis of United States claims data. Fertil Steril 105: 629-636.
  4. Latif T, Kold Jensen T, Mehlsen J, Holmboe SA, Brinth L, Pors K, Skouby SO, Jorgensen N, Lindahl-Jacobsen R. Semen quality is a predictor of subsequent morbidity. A Danish cohort study of 4,712 men with long-term follow-up. Am J Epidemiol. Doi: 10.1093/aje/kwx067. (Epub ahead of print]
  5. Levine H, Jorgensen N, Martino-Andrade A, Mendiola J, Weksler-Derri D, Mindlis I, Pinotti R, Swan SH. 2017. Temporal trends in sperm count: a systematic review and meta-regression analysis. Hum Reprod Update pp. 1-14. Doi: 10.1093/humupd/dmx022.


From: Marcus W Feldman <>

Date: Monday, July 31, 2017 at 8:10 PM

To: Aviva Lev-Ari <>

Subject: Fwd: text of sperm count essay

Psycho-Social Effects of Poverty, Unemployment and Epigenetics on Male Well-being, Physiological Conditions as POTENTIAL effects on Sperm Quality and Quantity and Evidence of its effects on Male Longevity

The Voice of Carol GrahamSergio Pinto, and John Juneau II , Monday, July 24, 2017, Report from the Brookings Institute

  1. The IMPACT of Well-being, Stress induced by Worry, Pain, Perception of Hope related to Employment and Lack of employment on deterioration of Physiological Conditions as evidence by Decrease Longevity

  2. Epigenetics and Environmental Factors

The geography of desperation in America

Carol GrahamSergio Pinto, and John Juneau II Monday, July 24, 2017, Report from the Brookings Institute

In recent work based on our well-being metrics in the Gallup polls and on the mortality data from the Centers for Disease Control and Prevention, we find a robust association between lack of hope (and high levels of worry) among poor whites and the premature mortality rates, both at the individual and metropolitan statistical area (MSA) levels. Yet we also find important differences across places. Places come with different economic structures and identities, community traits, physical environments and much more. In the maps below, we provide a visual picture of the differences in in hope for the future, worry, and pain across race-income cohorts across U.S. states. We attempted to isolate the specific role of place, controlling for economic, socio-demographic, and other variables.

One surprise is the low level of optimism and high level of worry in the minority dense and generally “blue” state of California, and high levels of pain and worry in the equally minority dense and “blue” states of New York and Massachusetts. High levels of income inequality in these states may explain these patterns, as may the nature of jobs that poor minorities hold.

We cannot answer many questions at this point. What is it about the state of Washington, for example, that is so bad for minorities across the board? Why is Florida so much better for poor whites than it is for poor minorities? Why is Nevada “good” for poor white optimism but terrible for worry for the same group? One potential issue—which will enter into our future analysis—is racial segregation across places. We hope that the differences that we have found will provoke future exploration. Readers of this piece may have some contributions of their own as they click through the various maps, and we welcome their input. Better understanding the role of place in the “crisis” of despair facing our country is essential to finding viable solutions, as economic explanations, while important, alone are not enough.



Read Full Post »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.


Scientists think excessive population growth is a cause of scarcity and environmental degradation. A male pill could reduce the number of unintended pregnancies, which accounts for 40 percent of all pregnancies worldwide.


But, big drug companies long ago dropped out of the search for a male contraceptive pill which is able to chemically intercept millions of sperm before they reach a woman’s egg. Right now the chemical burden for contraception relies solely on the female. There’s not much activity in the male contraception field because an effective solution is available on the female side.


Presently, male contraception means a condom or a vasectomy. But researchers from Center for Drug Discovery at Baylor College of Medicine, USA are renewing the search for a better option—an easy-to-take pill that’s safe, fast-acting, and reversible.


The scientists began with lists of genes active in the testes for sperm production and motility and then created knockout mice that lack those genes. Using the gene-editing technology called CRISPR, in collaboration with Japanese scientists, they have so far made more than 75 of these “knockout” mice.


They allowed these mice to mate with normal (wild type) female mice, and if their female partners don’t get pregnant after three to six months, it means the gene might be a target for a contraceptive. Out of 2300 genes that are particularly active in the testes of mice, the researchers have identified 30 genes whose deletion makes the male infertile. Next the scientists are planning a novel screening approach to test whether any of about two billion chemicals can disable these genes in a test tube. Promising chemicals could then be fed to male mice to see if they cause infertility.


Female birth control pills use hormones to inhibit a woman’s ovaries from releasing eggs. But hormones have side effects like weight gain, mood changes, and headaches. A trial of one male contraceptive hormone was stopped early in 2011 after one participant committed suicide and others reported depression. Moreover, some drug candidates have made animals permanently sterile which is not the goal of the research. The challenge is to prevent sperm being made without permanently sterilizing the individual.


As a better way to test drugs, Scientists at University of Georgia, USA are investigating yet another high-tech approach. They are turning human skin cells into stem cells that look and act like the spermatogonial cells in the testes. Testing drugs on such cells might provide more accurate leads than tests on mice.


The male pill would also have to start working quickly, a lot sooner than the female pill, which takes about a week to function. Scientists from University of Dundee, U.K. admitted that there are lots of challenges. Because, a women’s ovary usually release one mature egg each month, while a man makes millions of sperm every day. So, the male pill has to be made 100 percent effective and act instantaneously.



Read Full Post »

Reporter and Curator: Dr. Sudipta Saha, Ph.D.

During pregnancy, the baby is mostly protected from harmful microorganisms by the amniotic sac, but recent research suggests the baby could be exposed to small quantities of microbes from the placenta, amniotic fluid, umbilical cord blood and fetal membranes. One theory is that any possible prenatal exposure could ‘pre-seed’ the infant microbiome. In other words, to set the right conditions for the ‘main seeding event’ for founding the infant microbiome.

When a mother gives birth vaginally and if she breastfeeds, she passes on colonies of essential microbes to her baby. This continues a chain of maternal heritage that stretches through female ancestry for thousands of generations, if all have been vaginally born and breastfed. This means a child’s microbiome, that is the trillions of microorganisms that live on and in him or her, will resemble the microbiome of his/her mother, the grandmother, the great-grandmother and so on, if all have been vaginally born and breastfed.

As soon as the mother’s waters break, suddenly the baby is exposed to a wave of the mother’s vaginal microbes that wash over the baby in the birth canal. They coat the baby’s skin, and enter the baby’s eyes, ears, nose and some are swallowed to be sent down into the gut. More microbes form of the mother’s gut microbes join the colonization through contact with the mother’s faecal matter. Many more microbes come from every breath, from every touch including skin-to-skin contact with the mother and of course, from breastfeeding.

With formula feeding, the baby won’t receive the 700 species of microbes found in breast milk. Inside breast milk, there are special sugars called human milk oligosaccharides (HMO’s) that are indigestible by the baby. These sugars are designed to feed the mother’s microbes newly arrived in the baby’s gut. By multiplying quickly, the ‘good’ bacteria crowd out any potentially harmful pathogens. These ‘good’ bacteria help train the baby’s naive immune system, teaching it to identify what is to be tolerated and what is pathogen to be attacked. This leads to the optimal training of the infant immune system resulting in a child’s best possible lifelong health.

With C-section birth and formula feeding, the baby is not likely to acquire the full complement of the mother’s vaginal, gut and breast milk microbes. Therefore, the baby’s microbiome is not likely to closely resemble the mother’s microbiome. A baby born by C-section is likely to have a different microbiome from its mother, its grandmother, its great-grandmother and so on. C-section breaks the chain of maternal heritage and this break can never be restored.

The long term effect of an altered microbiome for a child’s lifelong health is still to be proven, but many studies link C-section with a significantly increased risk for developing asthma, Type 1 diabetes, celiac disease and obesity. Scientists might not yet have all the answers, but the picture that is forming is that C-section and formula feeding could be significantly impacting the health of the next generation. Through the transgenerational aspect to birth, it could even be impacting the health of future generations.


Read Full Post »

Finding the Actions That Alter Evolution

The biologist Marcus Feldman creates mathematical models that reveal how cultural traditions can affect the evolution of a species.

By Elizabeth Svoboda

January 5, 2017

In a commentary in Nature, you and your co-authors wrote, “We hold that organisms are constructed in development, not simply ‘programmed’ to develop by genes.” What does “constructed in development” mean?

It means there’s an interaction between the subject and the environment. The idea of a genetic blueprint is not tenable in light of all that is now known about how all sorts of environmental contingencies affect traits. For many animals it’s like that. Even plants — the same plant that is genetically identical, if you put it in this environment, it’s going to look totally different from if you put it in that environment.

We now have a better picture of the regulatory process on genes. Epigenetics changes the landscape in genetics because it’s not only the pure DNA sequence which influences what’s going on at the level of proteins and enzymes. There’s this whole other stuff, the other 95 percent of the genome, that acts like rheostats — you slide this thing up and down, you get more or less of this protein. It’s a critical thing in how much of this protein is going to be made. It’s interesting to think about the way in which cultural phenomena, which we used to think were things by themselves, can have this effect on how much messenger RNA is made, and therefore on many aspects of gene regulation.

Article to review and VIEW VIDEO



Quanta Magazine’s mission is to enhance public understanding of research developments in mathematics and the physical and life sciences. Quanta articles do not necessarily represent the views of the Simons Foundation. Learn more

Read Full Post »

The Extension of Biology Through Culture

Reporter: Aviva Lev-Ari, PhD, RN


Arnold and Mabel Beckman Center of the

National Academies of Sciences and Engineering

Distinctive Voices @ The Beckman Center


From: “Distinctive Voices @ The Beckman Center” <> on behalf of “Distinctive Voices @ The Beckman Center” <>

Reply-To: <>

Date: Wednesday, October 5, 2016 at 10:01 PM

To: Aviva Lev-Ari <>

Subject: RSVP NOW for Science Lecture – October 12


November 16, 2016

Evolution of Biology Through Culture

Andrew Whiten

University of St. Andrews 


The Extension of Biology Through Culture

Organized by Marcus Feldman, Francisco J. Ayala, Andrew Whiten and Kevin Laland


November 16-17, 2016



Nov 15   6:30 PM         Speaker Welcome Dinner at hotel (informal – no program)



Wednesday, November 16


7:30 AM         Bus departs Hotel for Beckman Center


7:30 AM         Registration and Buffet Breakfast, Beckman Center Dining Room


Session I


8:30 AM         Welcome Remarks, Marcus Feldman, Stanford University


9:00 AM         Evolution and revolution in cetacean vocal culture: lessons from humpback whale song, Ellen Garland, University of St Andrews, UK


9:50 AM         Gene-culture coevolution in whales and dolphins, Hal Whitehead, Dalhousie University
Halifax, Nova Scotia, Canada


10:40 AM         Break


11:00 AM         Cultural legacies: unpacking the inter-generational transmission of information in birds,
Lucy Aplin, University of Oxford, UK


11:50 AM         What evolves in the evolution of social learning? A social insect perspective, Elli
Leadbeater, Queen Mary University of London (QMUL)


12:40 PM         Buffet Lunch, Beckman Center Dining Room


Session II


1:50 PM         Can culture re-shape the evolution of learning and how?, Arnon Lotem, Tel Aviv


2:40 PM         What long term field studies reveal of primate traditions, Susan Perry, University of
California, Los Angeles


3:30 PM         Break (set up posters)


4:00 PM         Can we identify a primate signature in social learning? Dorothy Fragaszy, University of


4:50 PM         The evolution of primate intelligence, Kevin Laland, University of St Andrews, UK


5:40 PM         Poster Session and Buffet Dinner (Sackler registrants)


7:00 PM         Distinctive Voices Public Lecture

                       How animal cultures extend the scope of biology: Tradition and learning from apes to whales to bees, Andrew Whiten, University of St Andrews, UK


8:00 PM         Dessert and Coffee with combined audience


8:45 PM         Bus departs Beckman Center for Hotel



Thursday, November 17


7:00 AM         Bus departs Fairmont Newport Beach Hotel for Beckman Center


7:00 AM         Buffet Breakfast, Beckman Center Dining Room


Session III


8:00 AM        The role of cultural innovations, learning processes, and ecological dynamics in
shaping Middle Stone Age cultural adaptations
, Francesco d’Errico, University of                                     Bordeaux, France


8:50 AM         The ontogenetic foundations of cumulative cultural transmission, Cristine Legare,                        University of Texas, Austin


9:40 AM         Break


10:00 AM         “I don’t know”: ignorance and question-asking as engines for cognitive development,
Paul Harris, Harvard University


10:50 AM         Childhood as simulated annealing: How wide hypothesis exploration in an extended
childhood contributes to cultural learning
, Alison Gopnik, University of California,                                     Berkeley


11:40 AM         Buffet Lunch, Beckman Center Dining Room


Session IV


12:50 PM         How language shapes the nature of cultural inheritance, Susan Gelman, University of Michigan


1:40 PM         Big data and prospects for an evolutionary science of human history, Russel Gray, Max
Planck Institute for the Science of Human History in Jena, Germany


2:30 PM         Break


2:50 PM         Cultural Evolutionary Psychology, Cecilia Heyes, University of Oxford, UK


3:40 PM         Ongoing prospects for a unified science of cultural evolution, Alex Mesoudi, University of Exeter, UK


4:30 PM        Concluding Remarks, Francisco J. Ayala, University of California, Irvine


4:45 PM        Bus departs Beckman Center for Orange County Airport and Hotel


From: Marcus W Feldman <>

Date: Thursday, October 6, 2016 at 12:16 PM

To: Aviva Lev-Ari <>

Subject: Fwd: Sackler program for Irvine:11/16-17

Read Full Post »


Content Consultant: Larry H Bernstein, MD, FCAP

Genomics Orientations for Personalized Medicine

Volume One

electronic Table of Contents

Chapter 1

1.1 Advances in the Understanding of the Human Genome The Initiation and Growth of Molecular Biology and Genomics – Part I

1.2 CRACKING THE CODE OF HUMAN LIFE: Milestones along the Way – Part IIA

1.3 DNA – The Next-Generation Storage Media for Digital Information

1.4 CRACKING THE CODE OF HUMAN LIFE: Recent Advances in Genomic Analysis and Disease – Part IIC

1.5 Advances in Separations Technology for the “OMICs” and Clarification of Therapeutic Targets

1.6 Genomic Analysis: FLUIDIGM Technology in the Life Science and Agricultural Biotechnology

Chapter 2

2.1 2013 Genomics: The Era Beyond the Sequencing of the Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

2.2 DNA structure and Oligonucleotides

2.3 Genome-Wide Detection of Single-Nucleotide and Copy-Number Variation of a Single Human Cell 

2.4 Genomics and Evolution

2.5 Protein-folding Simulation: Stanford’s Framework for Testing and Predicting Evolutionary Outcomes in Living Organisms – Work by Marcus Feldman

2.6 The Binding of Oligonucleotides in DNA and 3-D Lattice Structures

2.7 Finding the Genetic Links in Common Disease: Caveats of Whole Genome Sequencing Studies

Chapter 3

3.1 Big Data in Genomic Medicine

3.2 CRACKING THE CODE OF HUMAN LIFE: The Birth of Bioinformatics & Computational Genomics – Part IIB 

3.3 Expanding the Genetic Alphabet and linking the Genome to the Metabolome

3.4 Metabolite Identification Combining Genetic and Metabolic Information: Genetic Association Links Unknown Metabolites to Functionally Related Genes

3.5 MIT Scientists on Proteomics: All the Proteins in the Mitochondrial Matrix identified

3.6 Identification of Biomarkers that are Related to the Actin Cytoskeleton

3.7 Genetic basis of Complex Human Diseases: Dan Koboldt’s Advice to Next-Generation Sequencing Neophytes

3.8 MIT Team Researches Regulatory Motifs and Gene Expression of Erythroleukemia (K562) and Liver Carcinoma (HepG2) Cell Lines

Chapter 4

4.1 ENCODE Findings as Consortium

4.2 ENCODE: The Key to Unlocking the Secrets of Complex Genetic Diseases

4.3 Reveals from ENCODE Project will Invite High Synergistic Collaborations to Discover Specific Targets  

4.4 Human Variome Project: encyclopedic catalog of sequence variants indexed to the human genome sequence

4.5 Human Genome Project – 10th Anniversary: Interview with Kevin Davies, PhD – The $1000 Genome

4.6 Quantum Biology And Computational Medicine

4.7 The Underappreciated EpiGenome

4.8 Unraveling Retrograde Signaling Pathways

4.9  “The SILENCE of the Lambs” Introducing The Power of Uncoded RNA

4.10  DNA: One man’s trash is another man’s treasure, but there is no JUNK after all

Chapter 5

5.1 Paradigm Shift in Human Genomics – Predictive Biomarkers and Personalized Medicine – Part 1 

5.2 Computational Genomics Center: New Unification of Computational Technologies at Stanford

5.3 Personalized Medicine: An Institute Profile – Coriell Institute for Medical Research: Part 3

5.4 Cancer Genomics – Leading the Way by Cancer Genomics Program at UC Santa Cruz

5.5 Genome and Genetics: Resources @Stanford, @MIT, @NIH’s NCBCS

5.6 NGS Market: Trends and Development for Genotype-Phenotype Associations Research

5.7 Speeding Up Genome Analysis: MIT Algorithms for Direct Computation on Compressed Genomic Datasets

5.8  Modeling Targeted Therapy

5.9 Transphosphorylation of E-coli Proteins and Kinase Specificity

5.10 Genomics of Bacterial and Archaeal Viruses

Chapter 6

6.1  Directions for Genomics in Personalized Medicine

6.2 Ubiquinin-Proteosome pathway, Autophagy, the Mitochondrion, Proteolysis and Cell Apoptosis: Part III

6.3 Mitochondrial Damage and Repair under Oxidative Stress

6.4 Mitochondria: More than just the “Powerhouse of the Cell”

6.5 Mechanism of Variegation in Immutans

6.6 Impact of Evolutionary Selection on Functional Regions: The imprint of Evolutionary Selection on ENCODE Regulatory Elements is Manifested between Species and within Human Populations

6.7 Cardiac Ca2+ Signaling: Transcriptional Control

6.8 Unraveling Retrograde Signaling Pathways

6.9 Reprogramming Cell Fate

6.10 How Genes Function

6.11 TALENs and ZFNs

6.12 Zebrafish—Susceptible to Cancer

6.13 RNA Virus Genome as Bacterial Chromosome

6.14 Cloning the Vaccinia Virus Genome as a Bacterial Artificial Chromosome 

6.15 Telling NO to Cardiac Risk- DDAH Says NO to ADMA(1); The DDAH/ADMA/NOS Pathway(2)

6.16  Transphosphorylation of E-coli proteins and kinase specificity

6.17 Genomics of Bacterial and Archaeal Viruses

6.18  Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

Chapter 7

7.1 Harnessing Personalized Medicine for Cancer Management, Prospects of Prevention and Cure: Opinions of Cancer Scientific Leaders @

7.2 Consumer Market for Personal DNA Sequencing: Part 4

7.3 GSK for Personalized Medicine using Cancer Drugs Needs Alacris Systems Biology Model to Determine the In Silico Effect of the Inhibitor in its “Virtual Clinical Trial”

7.4 Drugging the Epigenome

7.5 Nation’s Biobanks: Academic institutions, Research institutes and Hospitals – vary by Collections Size, Types of Specimens and Applications: Regulations are Needed

7.6 Personalized Medicine: Clinical Aspiration of Microarrays

Chapter 8

8.1 Personalized Medicine as Key Area for Future Pharmaceutical Growth

8.2 Inaugural Genomics in Medicine – The Conference Program, 2/11-12/2013, San Francisco, CA

8.3 The Way With Personalized Medicine: Reporters’ Voice at the 8th Annual Personalized Medicine Conference, 11/28-29, 2012, Harvard Medical School, Boston, MA

8.4 Nanotechnology, Personalized Medicine and DNA Sequencing

8.5 Targeted Nucleases

8.6 Transcript Dynamics of Proinflammatory Genes

8.7 Helping Physicians identify Gene-Drug Interactions for Treatment Decisions: New ‘CLIPMERGE’ program – Personalized Medicine @ The Mount Sinai Medical Center

8.8 Intratumor Heterogeneity and Branched Evolution Revealed by Multiregion Sequencing[1]

8.9 Diagnosing Diseases & Gene Therapy: Precision Genome Editing and Cost-effective microRNA Profiling

Chapter 9

9.1 Personal Tale of JL’s Whole Genome Sequencing

9.2 Inspiration From Dr. Maureen Cronin’s Achievements in Applying Genomic Sequencing to Cancer Diagnostics

9.3 Inform Genomics Developing SNP Test to Predict Side Effects, Help MDs Choose among Chemo Regimens

9.4 SNAP: Predict Effect of Non-synonymous Polymorphisms: How Well Genome Interpretation Tools could Translate to the Clinic

9.5  LEADERS in Genome Sequencing of Genetic Mutations for Therapeutic Drug Selection in Cancer Personalized Treatment: Part 2

9.6 The Initiation and Growth of Molecular Biology and Genomics – Part I

9.7 Personalized Medicine-based Cure for Cancer Might Not Be Far Away

9.8 Personalized Medicine: Cancer Cell Biology and Minimally Invasive Surgery (MIS)

 Chapter 10

10.1 Pfizer’s Kidney Cancer Drug Sutent Effectively caused REMISSION to Adult Acute Lymphoblastic Leukemia (ALL)

10.2 Imatinib (Gleevec) May Help Treat Aggressive Lymphoma: Chronic Lymphocytic Leukemia (CLL)

10.3 Winning Over Cancer Progression: New Oncology Drugs to Suppress Passengers Mutations vs. Driver Mutations

10.4 Treatment for Metastatic HER2 Breast Cancer

10.5 Personalized Medicine in NSCLC

10.6 Gene Sequencing – to the Bedside

10.7 DNA Sequencing Technology

10.8 Nobel Laureate Jack Szostak Previews his Plenary Keynote for Drug Discovery Chemistry

Chapter 11

11.1 mRNA Interference with Cancer Expression

11.2 Angiogenic Disease Research Utilizing microRNA Technology: UCSD and Regulus Therapeutics

11.3 Sunitinib brings Adult acute lymphoblastic leukemia (ALL) to Remission – RNA Sequencing – FLT3 Receptor Blockade

11.4 A microRNA Prognostic Marker Identified in Acute Leukemia 

11.5 MIT Team: Microfluidic-based approach – A Vectorless delivery of Functional siRNAs into Cells.

11.6 Targeted Tumor-Penetrating siRNA Nanocomplexes for Credentialing the Ovarian Cancer Oncogene ID4

11.7 When Clinical Application of miRNAs?

11.8 How mobile elements in “Junk” DNA promote cancer. Part 1: Transposon-mediated tumorigenesis,

11.9 Potential Drug Target: Glycolysis Regulation – Oxidative Stress-responsive microRNA-320

11.10  MicroRNA Molecule May Serve as Biomarker

11.11 What about Circular RNAs?

Chapter 12

12.1 The “Cancer Establishments” Examined by James Watson, Co-discoverer of DNA w/Crick, 4/1953

12.2 Otto Warburg, A Giant of Modern Cellular Biology

12.3 Is the Warburg Effect the Cause or the Effect of Cancer: A 21st Century View?

12.4 Hypothesis – Following on James Watson

12.5 AMPK Is a Negative Regulator of the Warburg Effect and Suppresses Tumor Growth In Vivo

12.6 AKT signaling variable effects

12.7 Rewriting the Mathematics of Tumor Growth; Teams Use Math Models to Sort Drivers from Passengers

12.8 Phosphatidyl-5-Inositol signaling by Pin1

Chapter 13

13.1 Nanotech Therapy for Breast Cancer

13.2 BRCA1 a tumour suppressor in breast and ovarian cancer – functions in transcription, ubiquitination and DNA repair

13.3 Exome sequencing of serous endometrial tumors shows recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes

13.4 Recurrent somatic mutations in chromatin-remodeling and ubiquitin ligase complex genes in serous endometrial tumors

13.5 Prostate Cancer: Androgen-driven “Pathomechanism” in Early onset Forms of the Disease

13.6 In focus: Melanoma Genetics

13.7 Head and Neck Cancer Studies Suggest Alternative Markers More Prognostically Useful than HPV DNA Testing

13.8 Breast Cancer and Mitochondrial Mutations

13.9  Long noncoding RNA network regulates PTEN transcription

Chapter 14

14.1 HBV and HCV-associated Liver Cancer: Important Insights from the Genome

14.2 Nanotechnology and HIV/AIDS treatment

14.3 IRF-1 Deficiency Skews the Differentiation of Dendritic Cells

14.4 Sepsis, Multi-organ Dysfunction Syndrome, and Septic Shock: A Conundrum of Signaling Pathways Cascading Out of Control

14.5  Five Malaria Genomes Sequenced

14.6 Rheumatoid Arthritis Risk

14.7 Approach to Controlling Pathogenic Inflammation in Arthritis

14.8 RNA Virus Genome as Bacterial Chromosome

14.9 Cloning the Vaccinia Virus Genome as a Bacterial Artificial Chromosome

Chapter 15

15.1 Personalized Cardiovascular Genetic Medicine at Partners HealthCare and Harvard Medical School

15.2 Congestive Heart Failure & Personalized Medicine: Two-gene Test predicts response to Beta Blocker Bucindolol

15.3 DDAH Says NO to ADMA(1); The DDAH/ADMA/NOS Pathway(2)

15.4 Peroxisome Proliferator-Activated Receptor (PPAR-gamma) Receptors Activation: PPARγ Transrepression for Angiogenesis in Cardiovascular Disease and PPARγ Transactivation for Treatment of Diabetes

15.5 BARI 2D Trial Outcomes

15.6 Gene Therapy Into Healthy Heart Muscle: Reprogramming Scar Tissue In Damaged Hearts

15.7 Obstructive coronary artery disease diagnosed by RNA levels of 23 genes – CardioDx, a Pioneer in the Field of Cardiovascular Genomic  Diagnostics

15.8 Ca2+ signaling: transcriptional control

15.9 Lp(a) Gene Variant Association

15.9.1 Two Mutations, in the PCSK9 Gene: Eliminates a Protein involved in Controlling LDL Cholesterol

15.9.2. Genomics & Genetics of Cardiovascular Disease Diagnoses: A Literature Survey of AHA’s Circulation Cardiovascular Genetics, 3/2010 – 3/2013

15.9.3 Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

15.9.4 The Implications of a Newly Discovered CYP2J2 Gene Polymorphism Associated with Coronary Vascular Disease in the Uygur Chinese Population

15.9.5  Gene, Meis1, Regulates the Heart’s Ability to Regenerate after Injuries.

15.10 Genetics of Conduction Disease: Atrioventricular (AV) Conduction Disease (block): Gene Mutations – Transcription, Excitability, and Energy Homeostasis

15.11 How Might Sleep Apnea Lead to Serious Health Concerns like Cardiac and Cancers?

Chapter 16

16.1 Can Resolvins Suppress Acute Lung Injury?

16.2 Lipoxin A4 Regulates Natural Killer Cell in Asthma

16.3 Biological Therapeutics for Asthma

16.4 Genomics of Bronchial Epithelial Dysplasia

16.5 Progression in Bronchial Dysplasia

Chapter 17

17.1 Breakthrough Digestive Disorders Research: Conditions Affecting the Gastrointestinal Tract.

17.2 Liver Endoplasmic Reticulum Stress and Hepatosteatosis

17.3 Biomarkers-identified-for-recurrence-in-hbv-related-hcc-patients-post-surgery

17.4  Usp9x: Promising Therapeutic Target for Pancreatic Cancer

17.5 Battle of Steve Jobs and Ralph Steinman with Pancreatic cancer: How We Lost

Chapter 18

18.1 Ubiquitin Pathway Involved in Neurodegenerative Disease

18.2 Genomic Promise for Neurodegenerative Diseases, Dementias, Autism Spectrum, Schizophrenia, and Serious Depression

18.3 Neuroprotective Therapies: Pharmacogenomics vs Psychotropic Drugs and Cholinesterase Inhibitors

18.4 Ustekinumab New Drug Therapy for Cognitive Decline Resulting from Neuroinflammatory Cytokine Signaling and Alzheimer’s Disease

18.5 Cell Transplantation in Brain Repair

18.6 Alzheimer’s Disease Conundrum – Are We Near the End of the Puzzle?

Chapter 19

19.1 Genetics and Male Endocrinology

19.2 Genomic Endocrinology and its Future

19.3 Commentary on Dr. Baker’s post “Junk DNA Codes for Valuable miRNAs: Non-coding DNA Controls Diabetes”

19.4 Therapeutic Targets for Diabetes and Related Metabolic Disorders

19.5 Secondary Hypertension caused by Aldosterone-producing Adenomas caused by Somatic Mutations in ATP1A1 and ATP2B3 (adrenal cortical; medullary or Organ of Zuckerkandl is pheochromocytoma)

19.6 Personal Recombination Map from Individual’s Sperm Cell and its Importance

19.7 Gene Trap Mutagenesis in Reproductive Research

19.8 Pregnancy with a Leptin-Receptor Mutation

19.9 Whole-genome Sequencing in Probing the Meiotic Recombination and Aneuploidy of Single Sperm Cells

19.10 Reproductive Genetic Testing

Chapter 20

20.1 Genomics & Ethics: DNA Fragments are Products of Nature or Patentable Genes?

20.2 Understanding the Role of Personalized Medicine

20.3 Attitudes of Patients about Personalized Medicine

20.4  Genome Sequencing of the Healthy

20.5   Genomics in Medicine – Tomorrow’s Promise

20.6  The Promise of Personalized Medicine

20.7 Ethical Concerns in Personalized Medicine: BRCA1/2 Testing in Minors and Communication of Breast Cancer Risk

 20.8 Genomic Liberty of Ownership, Genome Medicine and Patenting the Human Genome

Chapter 21

Recent Advances in Gene Editing Technology Adds New Therapeutic Potential for the Genomic Era:  Medical Interpretation of the Genomics Frontier – CRISPR – Cas9


21.1 Introducing CRISPR/Cas9 Gene Editing Technology – Works by Jennifer A. Doudna

21.1.1 Ribozymes and RNA Machines – Work of Jennifer A. Doudna

21.1.2 Evaluate your Cas9 gene editing vectors: CRISPR/Cas Mediated Genome Engineering – Is your CRISPR gRNA optimized for your cell lines?

21.1.3 2:15 – 2:45, 6/13/2014, Jennifer Doudna “The biology of CRISPRs: from genome defense to genetic engineering”

21.1.4  Prediction of the Winner RNA Technology, the FRONTIER of SCIENCE on RNA Biology, Cancer and Therapeutics  & The Start Up Landscape in BostonGene Editing – New Technology The Missing link for Gene Therapy?

21.2 CRISPR in Other Labs

21.2.1 CRISPR @MIT – Genome Surgery

21.2.2 The CRISPR-Cas9 System: A Powerful Tool for Genome Engineering and Regulation

Yongmin Yan and Department of Gastroenterology, Hepatology & Nutrition, University of Texas M.D. Anderson Cancer, Houston, USADaoyan Wei*

21.2.3 New Frontiers in Gene Editing: Transitioning From the Lab to the Clinic, February 19-20, 2015 | The InterContinental San Francisco | San Francisco, CA

21.2.4 Gene Therapy and the Genetic Study of Disease: @Berkeley and @UCSF – New DNA-editing technology spawns bold UC initiative as Crispr Goes Global

21.2.5 CRISPR & MAGE @ George Church’s Lab @ Harvard

21.3 Patents Awarded and Pending for CRISPR

21.3.1 Litigation on the Way: Broad Institute Gets Patent on Revolutionary Gene-Editing Method

21.3.2 The Patents for CRISPR, the DNA editing technology as the Biggest Biotech Discovery of the Century

2.4 CRISPR/Cas9 Applications

21.4.1  Inactivation of the human papillomavirus E6 or E7 gene in cervical carcinoma cells using a bacterial CRISPR/Cas 

21.4.2 CRISPR: Applications for Autoimmune Diseases @UCSF

21.4.3 In vivo validated mRNAs

21.4.6 Level of Comfort with Making Changes to the DNA of an Organism

21.4.7 Who will be the the First to IPO: Novartis bought in to Intellia (UC, Berkeley) as well as Caribou (UC, Berkeley) vs Editas (MIT)??

21.4.8 CRISPR/Cas9 Finds Its Way As an Important Tool For Drug Discovery & Development


Read Full Post »


Series A: e-Books on Cardiovascular Diseases

Series A Content Consultant: Justin D Pearlman, MD, PhD, FACC


Etiologies of Cardiovascular Diseases:

Epigenetics, Genetics and Genomics



Larry H Bernstein, MD, FCAP, Senior Editor, Author and Curator


Aviva Lev-Ari, PhD, RN, Editor and Curator

Introduction to Volume Three 

Genomics and Medicine

1.1  Genomics and Medicine: The Physician’s View

1.2  Ribozymes and RNA Machines – Work of Jennifer A. Doudna

1.3  Genomics and Medicine: Contributions of Genetics and Genomics to Cardiovascular Disease Diagnoses

1.4 Genomics Orientations for Individualized Medicine, Volume One

1.4.1 CVD Epidemiology, Ethnic subtypes Classification, and Medication Response Variability: Cardiology, Genomics and Individualized Heart Care: Framingham Heart Study (65 y-o study) & Jackson Heart Study (15 y-o study)

1.4.2 What comes after finishing the Euchromatic Sequence of the Human Genome?

1.5  Genomics in Medicine – Establishing a Patient-Centric View of Genomic Data


Epigenetics – Modifiable Factors Causing Cardiovascular Diseases

2.1 Diseases Etiology

2.1.1 Environmental Contributors Implicated as Causing Cardiovascular Diseases

2.1.2 Diet: Solids, Fluid Intake and Nutraceuticals

2.1.3 Physical Activity and Prevention of Cardiovascular Diseases

2.1.4 Psychological Stress and Mental Health: Risk for Cardiovascular Diseases

2.1.5 Correlation between Cancer and Cardiovascular Diseases

2.1.6 Medical Etiologies for Cardiovascular Diseases: Evidence-based Medicine – Leading DIAGNOSES of Cardiovascular Diseases, Risk Biomarkers and Therapies

2.1.7 Signaling Pathways

2.1.8 Proteomics and Metabolomics

2.1.9 Sleep and Cardiovascular Diseases

2.2 Assessing Cardiovascular Disease with Biomarkers

2.2.1 Issues in Genomics of Cardiovascular Diseases

2.2.2 Endothelium, Angiogenesis, and Disordered Coagulation

2.2.3 Hypertension BioMarkers

2.2.4 Inflammatory, Atherosclerotic and Heart Failure Markers

2.2.5 Myocardial Markers

2.3  Therapeutic Implications: Focus on Ca(2+) signaling, platelets, endothelium

2.3.1 The Centrality of Ca(2+) Signaling and Cytoskeleton Involving Calmodulin Kinases and Ryanodine Receptors in Cardiac Failure, Arterial Smooth Muscle, Post-ischemic Arrhythmia, Similarities and Differences, and Pharmaceutical Targets

2.3.2 EMRE in the Mitochondrial Calcium Uniporter Complex

2.3.3 Platelets in Translational Research ­ 2: Discovery of Potential Anti-platelet Targets

2.3.4 The Final Considerations of the Role of Platelets and Platelet Endothelial Reactions in Atherosclerosis and Novel Treatments

2.3.5 Nitric Oxide Synthase Inhibitors (NOS-I)

2.3.6 Resistance to Receptor of Tyrosine Kinase

2.3.7 Oxidized Calcium Calmodulin Kinase and Atrial Fibrillation

2.3.8 Advanced Topics in Sepsis and the Cardiovascular System at its End Stage

2.4 Comorbidity of Diabetes and Aging

2.4.1 Heart and Aging Research in Genomic Epidemiology: 1700 MIs and 2300 coronary heart disease events among about 29 000 eligible patients

2.4.2 Pathophysiological Effects of Diabetes on Ischemic-Cardiovascular Disease and on Chronic Obstructive Pulmonary Disease (COPD)

2.4.3 Risks of Hypoglycemia in Diabetics with Chronic Kidney Disease (CKD)

2.4.4  Mitochondrial Mechanisms of Disease in Diabetes Mellitus

2.4.5 Mitochondria: More than just the “powerhouse of the cell”

2.4.6  Pathophysiology of GLP-1 in Type 2 Diabetes

2.4.7 Developments in the Genomics and Proteomics of Type 2 Diabetes Mellitus and Treatment Targets

2.4.8 CaKMII Inhibition in Obese, Diabetic Mice leads to Lower Blood Glucose Levels

2.4.9 Protein Target for Controlling Diabetes, Fractalkine: Mediator cell-to-cell Adhesion though CX3CR1 Receptor, Released from cells Stimulate Insulin Secretion

2.4.10 Peroxisome proliferator-activated receptor (PPAR-gamma) Receptors Activation: PPARγ transrepression for Angiogenesis in Cardiovascular Disease and PPARγ transactivation for Treatment of Diabetes

2.4.11 CABG or PCI: Patients with Diabetes – CABG Rein Supreme

2.4.12 Reversal of Cardiac Mitochondrial Dysfunction

2.4.13  BARI 2D Trial Outcomes

2.4.14 Overview of new strategy for treatment of T2DM: SGLT2 inhibiting oral antidiabetic agents

2.5 Drug Toxicity and Cardiovascular Diseases

2.5.1 Predicting Drug Toxicity for Acute Cardiac Events

2.5.2 Cardiotoxicity and Cardiomyopathy Related to Drugs Adverse Effects

2.5.3 Decoding myocardial Ca2+ signals across multiple spatial scales: A role for sensitivity analysis

2.5.4. Leveraging Mathematical Models to Understand Population Variability in Response to Cardiac Drugs: Eric Sobie, PhD

2.5.5 Exploiting mathematical models to illuminate electrophysiological variability between individuals.

2.5.6 Clinical Effects and Cardiac Complications of Recreational Drug Use: Blood pressure changes, Myocardial ischemia and infarction, Aortic dissection, Valvular damage, and Endocarditis, Cardiomyopathy, Pulmonary edema and Pulmonary hypertension, Arrhythmias, Pneumothorax and Pneumopericardium


2.6 Male and Female Hormonal Replacement Therapy: The Benefits and the Deleterious Effects on Cardiovascular Diseases

2.6.1  Testosterone Therapy for Idiopathic Hypogonadotrophic Hypogonadism has Beneficial and Deleterious Effects on Cardiovascular Risk Factors

2.6.2 Heart Risks and Hormones (HRT) in Menopause: Contradiction or Clarification?

2.6.3 Calcium Dependent NOS Induction by Sex Hormones: Estrogen

2.6.4 Role of Progesterone in Breast Cancer Progression

Determinants of Cardiovascular Diseases Genetics, Heredity and Genomics Discoveries


3.1 Why cancer cells contain abnormal numbers of chromosomes (Aneuploidy)

3.1.1 Aneuploidy and Carcinogenesis

3.2 Functional Characterization of Cardiovascular Genomics: Disease Case Studies @ 2013 ASHG

3.3 Leading DIAGNOSES of Cardiovascular Diseases covered in Circulation: Cardiovascular Genetics, 3/2010 – 3/2013

3.3.1: Heredity of Cardiovascular Disorders

3.3.2: Myocardial Damage

3.3.3: Hypertention and Atherosclerosis

3.3.4: Ethnic Variation in Cardiac Structure and Systolic Function

3.3.5: Aging: Heart and Genetics

3.3.6: Genetics of Heart Rhythm

3.3.7: Hyperlipidemia, Hyper Cholesterolemia, Metabolic Syndrome

3.3.8: Stroke and Ischemic Stroke

3.3.9: Genetics and Vascular Pathologies and Platelet Aggregation, Cardiac Troponin T in Serum

3.3.10: Genomics and Valvular Disease

3.4  Commentary on Biomarkers for Genetics and Genomics of Cardiovascular Disease

Individualized Medicine Guided by Genetics and Genomics Discoveries

4.1 Preventive Medicine: Cardiovascular Diseases

4.1.1 Personal Genomics for Preventive Cardiology Randomized Trial Design and Challenges

4.2 Gene-Therapy for Cardiovascular Diseases

4.2.1 Genetic Basis of Cardiomyopathy

4.3 Congenital Heart Disease/Defects

4.4 Cardiac Repair: Regenerative Medicine

4.4.1 A Powerful Tool For Repairing Damaged Hearts

4.4.2 Modified RNA Induces Vascular Regeneration After a Heart

4.5 Pharmacogenomics for Cardiovascular Diseases

4.5.1 Blood Pressure Response to Antihypertensives: Hypertension Susceptibility Loci Study

4.5.2 Statin-Induced Low-Density Lipoprotein Cholesterol Reduction: Genetic Determinants in the Response to Rosuvastatin

4.5.3 SNPs in apoE are found to influence statin response significantly. Less frequent variants in PCSK9 and smaller effect sizes in SNPs in HMGCR

4.5.4 Voltage-Gated Calcium Channel and Pharmacogenetic Association with Adverse Cardiovascular Outcomes: Hypertension Treatment with Verapamil SR (CCB) vs Atenolol (BB) or Trandolapril (ACE)

4.5.5 Response to Rosuvastatin in Patients With Acute Myocardial Infarction: Hepatic Metabolism and Transporter Gene Variants Effect

4.5.6 Helping Physicians identify Gene-Drug Interactions for Treatment Decisions: New ‘CLIPMERGE’ program – Personalized Medicine @ The Mount Sinai Medical Center

4.5.7 Is Pharmacogenetic-based Dosing of Warfarin Superior for Anticoagulation Control?

Summary & Epilogue to Volume Three



Read Full Post »

Older Posts »